Plain English: In this work, we collected Resting-State fMRI data from patients with OCD before they engaged in 4 weeks of Cognitive Behavioral Therapy (CBT). We calculated functional connectivity within the Default Mode and Visual Networks and trained a machine-learning classifier to learn how those patterns relate to a patient’s success in the CBT. The classifier was able to learn so well from these patterns that it could predict a patient’s OCD symptom severity (as measured by YBOCS) after CBT– effectively predicting their symptoms 4 weeks in the future. Such insights could help guide treatment options.